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Rough set theory in the classification of diagnoses
Responsible organisation
2009 (English)Conference paper, (Refereed) Published
Abstract [en]

Rough sets, surrounded by two approximation sets filled with sure and possible members constitute perfect mathematical tools of the classification of some objects. In this work we adopt the rough technique to verify diagnostic decisions concerning a sample of patients whose symptoms are typical of a considered diagnosis. The objective is to extract the patients who surely Suffer from the diagnosis, to indicate the patients who are free from it, and even to make decisions in undefined diagnostic cases. By applying selected logical decision rules, we also discuss a possibility of reducing of symptom sets to their minimal collections preserving the previous results in order to minimize a number of numerical calculations.

Place, publisher, year, edition, pages
Berlin: Springer , 2009.
Keyword [en]
fuzzy sets, rough set theory, medical diagnosis
National Category
Mathematics Mathematical Analysis
Identifiers
URN: urn:nbn:se:bth-8984ISI: 000273952000005Local ID: oai:bth.se:forskinfo4BD52A91D726B9D6C125733E004CEF2BISBN: 978-3-642-04461-8 (print)OAI: oai:DiVA.org:bth-8984DiVA: diva2:836760
Conference
International Conference on Computers in Medical Activity 2007
Note
Conference Information: International Conference on Computers in Medical Activity Lodz, POLAND, 2007 Coll Comp Sci; Polish Soc Med Comp Sci Source: COMPUTERS IN MEDICAL ACTIVITY Book Series: Advances in Intelligent and Soft Computing Volume: 65 Pages: 41-51 Published: 2009Available from: 2012-09-18 Created: 2007-08-21 Last updated: 2016-09-20Bibliographically approved

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  • apa
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